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Former author of one of the top 5 facial recognition servers in the world for multiple years running, here's what's going on: the industry has solved this issue

Former author of one of the top 5 facial recognition servers in the world for multiple years running, here's what's going on: the industry has solved this issue, but the potential clients are seeking the lowest bidder, and picking the newer companies, the nepostically created not really players but well connected, and those companies have terrible implementations. This is not a case of the technology not there yet, we solved all these racial bias issues 10 years ago. But new companies with new training sets and new ML engineers that do not know any of the industry's history are now landing contracts with terrible quality models, but well connected sales channels.

graemep 7mo ago
So just like the rest of government IT then.
raw_anon_1111 7mo ago
How recently? We had a home security camera and every time our (Black) son walked up to the door, the camera would classify him as an “animal”. This was as recently as 2022
- onetokeoverthe 7mo ago
  [dead]
- fallinghawks 7mo ago
  In the other direction, my camera regularly identifies cats, crows, and shadows as people. I think recognition in security cameras has a very long way to go.
  - washadjeffmad 7mo ago
    My friend recently sent me a screenshot of her Arlo detecting her backside as a 'vehicle'.
- bsenftner 7mo ago
  You're running toy facial recognition. The FR that comes with consumer products is a marketing claim nonsense joke.
griffzhowl 7mo ago
This study finds a higher rate of correct identification for black people than for other ethnic groups, whereas a few years ago the problem seemed to be that the software was less effective at identifying black people. Do you have some insight about why this reversal might have occurred?
- bsenftner 7mo ago
  To have a high quality facial recognition system it needs to include every possible combination of ethnicity, in addition to all of those they each need to include variations of daylight, of dappled light, of partial obscuring, night time illumination, across every variation of season, variations of expression and face angle, across variations of weather, variations of distance, across variations of things placed on a person's face, and then across all kinds of variations of video compression. All these face image variations in the training set enable the trained model to find and track the features that persist through all these variations. In truth it requires hundreds of millions of facial images to create an accurate facial recognition system. Most new companies and many that have been around for respectable periods are not realizing how much data collection, annotation and additional variation creation it requires for a high quality FR training set. The company I worked at spent 20 years collecting laser scans of real people to then create the augmented real person data set with several hundred million faces.
- MrSkelter 7mo ago
  Your problem is evident in your question. What does “black” mean? It’s entirely subjective. Dwayne Johnson? Liv Tyler? Nelson Mandela? Barack Obama? Mariah Carey? This is a semantic issue. Ethnic groups are constructs. A system which misidentifies people identifies all people poorly. It doesn’t track across regions either. People labelled “white” by law in some countries (Brazil, South Africa, etc) would be classified as “black” elsewhere. In England, the example here, we do not classify people the way the Us does, with its history of “one drop” politics. Many British people considered “white” are “black” in the US. There is no scientifically valid way of defining who counts as “black” so any discussion of tuning a system based on this definition is a disaster. Even the people commenting are talking about different groups based on their own culture and prejudices.
danaris 7mo ago
Can you link the peer-reviewed citations for having solved the racial bias issues, in anything but specific bespoke cases? Frankly, I'm skeptical, but I'm willing to be convinced by reputable evidence.

graemep 7mo ago

So just like the rest of government IT then.

raw_anon_1111 7mo ago

How recently? We had a home security camera and every time our (Black) son walked up to the door, the camera would classify him as an “animal”. This was as recently as 2022

onetokeoverthe 7mo ago
[dead]
fallinghawks 7mo ago
In the other direction, my camera regularly identifies cats, crows, and shadows as people. I think recognition in security cameras has a very long way to go.
- washadjeffmad 7mo ago
  My friend recently sent me a screenshot of her Arlo detecting her backside as a 'vehicle'.
bsenftner 7mo ago
You're running toy facial recognition. The FR that comes with consumer products is a marketing claim nonsense joke.

griffzhowl 7mo ago

This study finds a higher rate of correct identification for black people than for other ethnic groups, whereas a few years ago the problem seemed to be that the software was less effective at identifying black people. Do you have some insight about why this reversal might have occurred?

bsenftner 7mo ago
To have a high quality facial recognition system it needs to include every possible combination of ethnicity, in addition to all of those they each need to include variations of daylight, of dappled light, of partial obscuring, night time illumination, across every variation of season, variations of expression and face angle, across variations of weather, variations of distance, across variations of things placed on a person's face, and then across all kinds of variations of video compression. All these face image variations in the training set enable the trained model to find and track the features that persist through all these variations. In truth it requires hundreds of millions of facial images to create an accurate facial recognition system. Most new companies and many that have been around for respectable periods are not realizing how much data collection, annotation and additional variation creation it requires for a high quality FR training set. The company I worked at spent 20 years collecting laser scans of real people to then create the augmented real person data set with several hundred million faces.
MrSkelter 7mo ago
Your problem is evident in your question. What does “black” mean? It’s entirely subjective. Dwayne Johnson? Liv Tyler? Nelson Mandela? Barack Obama? Mariah Carey? This is a semantic issue. Ethnic groups are constructs. A system which misidentifies people identifies all people poorly. It doesn’t track across regions either. People labelled “white” by law in some countries (Brazil, South Africa, etc) would be classified as “black” elsewhere. In England, the example here, we do not classify people the way the Us does, with its history of “one drop” politics. Many British people considered “white” are “black” in the US. There is no scientifically valid way of defining who counts as “black” so any discussion of tuning a system based on this definition is a disaster. Even the people commenting are talking about different groups based on their own culture and prejudices.

danaris 7mo ago

Can you link the peer-reviewed citations for having solved the racial bias issues, in anything but specific bespoke cases? Frankly, I'm skeptical, but I'm willing to be convinced by reputable evidence.